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AtheroRisk: An Integrated computer Software System for Stroke Risk Stratification Utilizing Carotid Plaque Analysis in Ultrasound Videos

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SN computer Science 2025年第2期6卷 1-16页

作者： Gemenaris, Michalis Liapi, Georgia D. Markides, Christos Constantinou, Kyriacos Loizou, Christos P. Neophytou, Michalis Kardoulas, Dimitrios Pattichis, Marios S. Griffin, Maura Nicolaides, Andrew Pattichis, Constantinos S. Kyriacou, Efthyvoulos Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol Cyprus Department of Computer Science and Engineering Frederick University Nicosia Cyprus Department of Computer Science University of Cyprus Nicosia Cyprus American Medical Center Nicosia Cyprus Vascular Surgery Clinic Attikon General University Hospital Athens Greece Department of Electrical and Comp. Engineering Univ. of New Mexico Albuquerque NM United States Vascular Screening and Diagnostic Center Nicosia Cyprus

In this study we propose and evaluate AtheroRisk, a standalone integrated computer software system for the analysis of carotid B-mode ultrasound (U/S) images and videos. Our goal was to provide a tool to help physicians stratify stroke risk. The presented system is based on outcomes from different research studies, as well as European guidelines for the evaluation and treatment of carotid artery disease. The goal is to enable reproducible analysis of atherosclerotic plaques in real time. AtheroRisk brings together analysis of U/S image and/or video of the carotid arteries facilitating anonymization, standardization, noise filtering and segmentation of plaques;followed by image and motion feature extraction to derive plaque-composition and stability. All the above steps are combined to determine the annual stroke risk rate and the 5-year stroke-free survival rate. The system is powered by an SQLite local database, in which the end user can save and manage data extracted from processing and analysis in an anonymized way. The first version of AtheroRisk was developed following an incremental software development process. The developed system was verified using 54 U/S videos (27 Asymptomatic, AS;27 Symptomatic, SY cases) while the clinician’s satisfaction and comments were collected through a questionnaire-based validation process. The results show that the integrated system proposed in this study can be successfully used for the automated image and video analysis of the CCA plaque in ultrasound videos. © The Author(s) 2025.

关键词： Carotid plaque analysis Motion analysis Plaque features Stroke risk stratification Ultrasound video

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Pharos: A Transparent and Steerable Visualization Recommendation System

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Journal of Computing Science and engineering 2023年第1期17卷 1-12页

作者： Chang, Youli L’Yi, Sehi Kim, Young Taek Song, Hyunjoo Kim, Bohyoung Seo, Jinwook Department of Computer Science and Engineering Seoul National University Seoul Korea Republic of Department of Biomedical Informatics Harvard Medical School BostonMA United States School of Computer Science and Engineering Soongsil University Seoul Korea Republic of Division of Biomedical Engineering Hankuk University of Foreign Studies - Global Campus Yongin Korea Republic of

We propose Pharos, a novel visualization recommendation system that makes use of several provenance data sources and multi-perspective overviews to boost the transparency and steerability of the recommendation engine. Pharos helps a user understand recommendation contexts along with the user’s analysis progress in three complementary overviews. Pharos also serves categorized and scalable recommendations, either expanding or narrowing a user’s analysis scope. Based on provenance data and explicit user annotations (i.e., bookmarked or excluded visualizations), Pharos dynamically updates a recommendation list. According to the provided context, a user can steer the recommendation direction by filtering recommended candidates and rearranging them via the weight controller of the similarity measure on the recommendation engine. We showed how Pharos helped users understand and steer visualization recommendations through two comparative user studies. © 2023. The Korean Institute of Information Scientists and Engineers

关键词： Recommender systems

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Big Five Personality Prediction Based on Indonesian Tweets and Personality Test

Big Five Personality Prediction Based on Indonesian Tweets a...

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2023 International Conference on Electrical engineering and informatics, ICEEI 2023

作者： Parameswara, Made Arbi Mahendra, Farrel Satya Putra Mardika, Muhammad Randy Cahya Puspasari, Ira Utama, Nugraha Priya School of Electrical Engineering and Informatics Bandung Institute of Technology Bandung Indonesia Dinamika University Computer Engineering Department Surabaya Indonesia

ISBN: (纸本)9798350381290

The integration of human resources and artificial intelligence has shown a growing interest in automatically predicting personality traits, particularly in recruitment. To contribute to this field, we propose a new method to assist human resource professionals in Indonesia to identify candidates' personality traits. Biases come from personality tests due to their question format and susceptibility to manipulation on this research, we propose an approach that combines personality tests using the BFI form, which measures OCEAN personality traits, with personality trait predictions derived from Twitter data. This research aims to create a personality prediction model and system that efficiently and effectively screens candidate personality traits in human resources. This research has developed a novel model that combines personality test results with tweets personality prediction with an impressive F1-macro performance of 98%. © 2023 IEEE.

关键词： Machine learning

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Late Breaking Results: Language-level QoR modeling for High-Level Synthesis 24

Late Breaking Results: Language-level QoR modeling for High-...

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61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Masouros, Dimosthenis Ferikoglou, Aggelos Zervakis, Georgios Xydis, Sotirios Soudris, Dimitrios Microprocessors and Digital Systems Laboratory Ece National Technical University of Athens Greece Department of Computer Engineering and Informatics University of Patras Greece

ISBN: (纸本)9798400706011

This paper proposes a language-level modeling approach for HighLevel Synthesis based on the state-of-the-art Transformer architecture. Our approach estimates the performance and required resources of HLS applications directly from the source code when different synthesis directives, in terms of HLS #pragmas, are applied. Results show that the proposed architecture achieves 96.02% accuracy for predicting the feasibility class of applications and an average of 0.95 and 0.91 R2 scores for predicting the actual performance and required resources, respectively. © 2024 Copyright held by the owner/author(s).

关键词： High level synthesis

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Fully integrated Windows framework for source localization with MNE Python and FreeSurfer

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Current Directions in Biomedical engineering 2023年第1期9卷 371-374页

作者： Oppermann, Hannes Wulf, Simon Komosar, Milana Haueisen, Jens Haueisen, Jens Department of Computer Science and Automation Institute of Biomedical Engineering and Informatics Technische Universität Ilmenau Ilmenau Germany Department of Neurology Biomagnetic Center University Hospital Jena Jena Germany

There is a variety of software packages, toolboxes, or libraries for the analysis and processing of neurophysiological data such as EEG and MEG. Many of these solutions provide algorithms for both, sensor-space analysis and sourcespace analysis. Especially with the solutions that run on Windows machines, it is noticeable that the step of the volume model generation is usually not included, since the state-ofthe- art software for this (FreeSurfer) is a Unix-based software and thus not available forWindows machines. Therefore, our goal was to develop a fully-integrated software solution for Windows machines, accessing all processing steps already implemented in an existing toolbox and using FreeSurfer in the same system. Due to its widespread use, we chose MNE Python as the basis for our fully integrated software solution. We used the Windows Subsystem for Linux to create a virtual Linux kernel for the FreeSurfer installation. To demonstrate the workflow, the libeep, and AutoReject libraries have been added. A 64-channel EEG recording during right-hand movement (ME) and imagination (MI) was used to test the implemented workflow. The developed framework consists of several modules within Python, mainly using existing scripts and functions. The library libeep was integrated to read the EEG data with the '.cnt', eeprope format. AutoReject was used to automatically interpolate detected bad channels or to reject complete epochs. FreeSurfer was successfully integrated and customized Python scripts enabled the communication between MNE Python on a Windows machine and FreeSurfer on a virtual Linux kernel. With the above-mentioned EEG dataset, we performed source reconstruction and were able to show ERD/S patterns for both, ME and MI. Our new, fullyintegrated software framework can be used on Windows machines to perform a complete process of source reconstruction. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Python

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Advancing Color Perception: An IoT-driven Pedagogical System for Visually Impaired Children 1

Advancing Color Perception: An IoT-driven Pedagogical System...

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1st IEEE International Conference on Advances in Signal Processing, Power, Communication, and Computing, ASPCC 2024

作者： Balage, Prasandika Jayawardene, Nuwan University of Westminster School of Computer Science and Engineering London United Kingdom Informatics Institute of Technology Department of Computing Colombo Sri Lanka

ISBN: (纸本)9798350355093

Visual impairment is characterized by the loss of vision, encompassing both complete blindness and partial vision loss. Studies reveal a notable prevalence of visual impairment among school-aged children. The significance of colors in acquiring and discerning visual information is crucial, aiding children in effectively perceiving and comprehending their surroundings. This study presents an Internet of Things (IoT) system designed for teaching colors to visually impaired children. The system achieved an accuracy rate surpassing 77.8%, and it is operated effectively regardless of surrounding lighting conditions. Given that the target users of the system are visually impaired children, this research was conducted in close alignment with Human-computer Interaction (HCI) principles. © 2024 IEEE.

关键词： Color vision

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Concierge: Towards Accuracy-Driven Bandwidth Allocation for Video Analytics Applications in Edge Network 8

Concierge: Towards Accuracy-Driven Bandwidth Allocation for ...

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8th IEEE International Conference on Edge Computing and Communications, EDGE 2024

作者： Huang, Yuyang Zharfan, Faishal Hendrawan, Hendrawan Gunawi, Haryadi S. Jiang, Junchen University of Chicago Department of Computer Science Chicago United States Bandung Institute of Technology School of Electrical Engineering and Informatics Bandung Indonesia

ISBN: (纸本)9798350368499

When performing inference on sensor data, edge video analytics applications may not always need high-fidelity data, since important information may not appear all the time. Consequently, each edge AI application's bandwidth demand is highly dynamic. Thus, a shared edge system should dynamically allocate more bandwidth to the applications in need to reach high accuracy at each moment. However, previous bandwidth allocators are ill-suited because they are agnostic to the timevarying impact of bandwidth on each application's *** short paper explores a new accuracy-driven approach to bandwidth allocation, which periodically re-allocates bandwidth across edge AI applications based on the sensitivity of each application's accuracy to its bandwidth share. To examine its practical benefit and technical challenges, we present a concrete accuracy-driven bandwidth allocator called ConciERGE, which exposes a simple yet efficient interface to estimate each application's sensitivity to a small change in its bandwidth *** run CONCIERGE on state-of-the-art video-analytics applications with real video streams and show its early promise in greatly improving the inference accuracy of video analytics. © 2024 IEEE.

关键词： Bandwidth

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A Systematic Literature Review of XAI-based Approaches on Brain Disease Detection using Brain MRI Images 4

A Systematic Literature Review of XAI-based Approaches on Br...

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4th International Conference on Advanced Research in Computing, ICARC 2024

作者： Madapatha, Savin Fernando, Pumudu University of Westminster Department of Computer Science and Engineering London United Kingdom School of Computing Informatics Institute of Technology Colombo Sri Lanka

ISBN: (纸本)9798350384864

Brain Magnetic Resonance Imaging (MRI) analysis is a widely used medical procedure for the early diagnosis of various brain diseases. Accurate pathology identification during the brain MRI analysis procedure is crucial as misdiagnoses or missed findings can greatly affect a patient's treatment and long-term prediction. With the recent advancement of Artificial Intelligence (AI) in the medical field, researchers have approached various techniques to detect brain diseases using AI. Although AI models exhibit high accuracy, they suffer from a lack of transparency and interpretability, paving the way for the development of eXplainable Artificial Intelligence (XAI) methods in brain disease diagnosis. Image segmentation, machine learning, deep learning and XAI are important for assisting the diagnostic procedure. In this paper, a comprehensive overview of various existing techniques in brain disease detection using MRI is presented, starting with image segmentation techniques, followed by classification techniques, and finally, XAI techniques. In conclusion, the paper identifies a critical need for further research on XAI integration to advance brain disease detection. © 2024 IEEE.

关键词： Magnetic resonance imaging

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Longitudinal Evaluation of Casual Puzzle Tablet Games by Older Adults

Longitudinal Evaluation of Casual Puzzle Tablet Games by Old...

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2024 ACM Designing Interactive Systems Conference, DIS 2024

作者： Chaudhry, Beenish Moalla Islam, Muhammad Usama Chawla, Nitesh Vinay School of Computing and Informatics University of Louisiana Lafayette United States Department of Computer Science and Engineering University of Notre Dame United States

ISBN: (纸本)9798400705830

Despite growing interest in mobile games for older adults, there is limited exploration of older adults’ gaming behaviors, perceptions, and experiences as they engage with casual puzzle games over a period of time. To address this, we conducted a 9-month study with 20 older adults, examining training needs, in-situ experiences, and preferences. Participants were trained on tablet PCs and ten selected games. During the study, participants documented their experiences and attended technology workshops. Gaming behaviors were logged and analyzed using descriptive and inferential statistics, revealing patterns and statistically signifcant diferences in play frequency and duration over the course of the study. Thematic analysis identifed facilitators and barriers to engagement such as customization, co-play experiences, and health issues. Based on these fndings, we recommend incorporating educational elements, enhancing user control, leveraging identity and nostalgia, supporting social interactions, designing for tangible interaction, and emphasizing the importance of learning aids. Future research should test the efectiveness of these recommendations in increasing older adults’ engagement with casual games. © 2024 Copyright held by the owner/author(s).

关键词： Personal computers

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A distributed B+Tree indexing method for processing range queries over streaming data

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Cluster Computing 2024年第2期27卷 1251-1274页

作者： Safaee, Shahab Mirabi, Meghdad Rahmani, Amir Masoud Safaei, Ali Asghar Department of Computer Engineering Faculty of Engineering South Tehran Branch Islamic Azad University Tehran Iran Future Technology Research Center National Yunlin University of Science and Technology Yunlin Douliou Taiwan Department of Medical Informatics Faculty of Medical Sciences Tarbiat Modares University Tehran Iran

A data stream exhibits as a massive unbounded sequence of data elements continuously generated at a high rate. Stream databases raise new challenges for query processing due to both the streaming nature of data which constantly changes over time and the wider range of queries submitted by the user when compared with the traditional databases. In this paper, we propose a system architecture which includes components for both distributed indexing of streaming data and distributed processing of range queries on streaming data. Instead of creating a large and centralized B+Tree index structure, we create a set of small B+Tree indexes in such a way that a B+Tree index can be created for every partition of streaming data. We also design a distributed range search algorithm which can be used by each individual machine inside a Spark cluster to independently process range queries on each partition of streaming data. By exploiting the proposed system architecture, the process of indexing of streaming data and the process of querying over streaming data can be performed in a distributed and parallel manner. By performing several experiments, we demonstrate that our proposed indexing method is scalable and efficient for processing range queries on streaming data compared to the existing centralized B+Tree indexing methods and therefore, it can be used for applications involving data streams with a large volume of data elements and a large number of range queries. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023.

关键词： Query processing

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